Question 1

An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

Options :

A : Train the model over multiple desktop computers

B : Train the model on GPUs

C : Use a contractor to do the training portion

D : Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer

Answer: B

Question 2

You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique. What is this technique called?

Options :

A : Reinforcement Learning

B : Generative AI

C : Transfer Learning

D : Pre-Trained Models

Answer: C

Question 3

You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results. What's your best course of action?

Options :

A : Keep going as planned and the problem will eventually correct itself

B : Try to get additional data - at least 5 training examples for each dimension in the representation

C : Try to get additional information from project lead to see how many examples per dimension are needed

D : Try to improve the quality of your data through more preparation

Answer: B

Question 4

You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?

Options :

A : Use noise reduction techniques to reduce all forms of data noise

B : Implement a new data privacy policy

C : Store the data in a data warehouse

D : If this data is not needed, use Data anonymization techniques to remove it before feeding to models

Answer: D

Question 5

A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

Options :

A : It's underestimating the project timeline by 3 months

B : It fits into a waterfall timeframe, but not an agile project timeframe

C : It's not accounting for data preparation timelines

D : It's not accounting for potential project delays

Answer: D

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